Cleaning of direct compression continuous manufacturing equipment through displacement of API residues by excipients.

This feasibility study evaluates a cleaning process designed to avoid the use of detergents and reduce operator exposure to the active pharmaceutical ingredient (API). The continuous manufacturing equipment was cleaned using excipients to displace ibuprofen residues from the system. The cleaning process was performed using 3.0 kg of Prosolv® and 3.0 kg of Tablettose® 70. The impact of different volumetric feed rates of the cleaning excipient was assessed. The displacement of API and blend residues was evaluated with in-line near infrared (NIR) spectroscopy. Principal component analysis (PCA) was performed to evaluate the cleaning progress as the Prosolv® flowed through the feeder, mixer and stream sampler. In-place Raman spectra were acquired from the material sticking to detect the ibuprofen residues. The study showed that Prosolv® and Tablettose® can remove ibuprofen residues effectively from the hopper, feeder screw, mixer paddles, shaft and stream sampler. The Process Analytical Technology (PAT) system can be utilized to detect API displacement during the cleaning process. However, dismantling and manual cleaning was required to remove material sticking at the surfaces adjacent to the rotating feeder screws and mixer paddles.

The Use of a Closed Feed Frame for the Development of Near-Infrared Spectroscopic Calibration Model to Determine Drug Concentration.

PURPOSE: This study evaluates the use of the closed feed frame as a material sparing approach to develop near-infrared (NIR) spectroscopic calibration models for monitoring blend uniformity. The effect of shear induced by recirculation on NIR spectra was also studied. METHODS: Calibration models were developed using NIR spectra obtained in the closed feed frame for two cases. For case 2, blends that flowed through the open feed frame were predicted with the model. The shear effect of the feed frame on the blends was assessed through the characterization of powder properties before and after recirculation. RESULTS: The physical characterization of the blends confirmed that the powder properties were not altered after recirculation within the closed feed frame. Both calibration models provided highly accurate predictions of the test sets with low bias (0.03% w/w and -0.06% w/w) and relative standard error of prediction (1.9% and 3.7%), respectively. The predictive performance of the calibration models was not affected by the shear effect. CONCLUSION: Recirculation within the closed feed frame did not change the physical properties of the blends studied. The prediction of blends flowing through the open feed frame was possible with a calibration model developed in the closed feed frame. The closed feed frame could reduce the materials needed to develop calibration models by more than 90%.

Identification of Four Similar Cell Culture Media According to their Glucose, Glutamine, and Pyruvate Content by Handheld Raman Spectroscopy.

PURPOSE: This study describes the first efforts to build a spectral library to identify four cell culture media in powder form with spectra obtained with a handheld Raman spectrometer. These complex mixtures contain over 30 components and are among the most widely used cell culture media. METHODS: A total of 32 spectra were collected for the four Dulbecco's Modified Eagle Medium cell culture media and pure materials (glucose and L-glutamine) in powder form. The spectra were preprocessed using standard normal variate with second derivative, and the barcode method before performing principal component analysis (PCA). RESULTS: The PCA model differentiated the pure glucose and the cell culture media according to the glucose concentration along the first principal component. The second principal component differentiated the three cell culture media with high glucose content according to the pyruvate concentration. The correlation coefficient showed that powdered cell culture media with high glucose concentration have a higher correlation with pure glucose, when compared with the cell culture media with low glucose. CONCLUSION: The Raman spectra made it possible to differentiate the four DMEM in the cell culture media from the majority of the external samples used in the method evaluation. However, sample heterogeneity affected the predictions. Additional studies are needed to improve the method's ability to differentiate the DMEM with high glucose.

Evaluation of a compact composite sensor array for concentration monitoring of solutions and suspensions via multivariate analysis.

Compact composite probes were identified as a priority to alleviate space constraints in miniaturized unit operations and pharmaceutical manufacturing platforms. Therefore, in this proof of principle study, a compact composite sensor array (CCSA) combining ultraviolet and near infrared features at four different wavelengths (280, 340, 600, 860 nm) in a 380 × 30 mm housing (length x diameter, 7 mm diameter at the probe head), was evaluated for its capabilities to monitor in situ concentration of solutions and suspensions via multivariate analysis using partial least squares (PLS) regression models. Four model active pharmaceutical ingredients (APIs): warfarin sodium isopropanol solvate (WS), lidocaine hydrochloride monohydrate (LID), 6-mercaptopurine monohydrate (6-MP), and acetaminophen (ACM) in their aqueous solution and suspension formulation were used for the assessment. The results demonstrate that PLS models can be applied for the CCSA prototype to measure the API concentrations with similar accuracy (validation samples within the United States Pharmacopeia (USP) limits), compared to univariate CCSA models and multivariate models for an established Raman spectrometer. Specifically, the multivariate CCSA models applied to the suspensions of 6-MP and ACM demonstrate improved accuracy of 63% and 31%, respectively, compared to the univariate CCSA models [1]. On the other hand, the PLS models for the solutions WS and LID showed a reduced accuracy compared to the univariate models [1].

Assessment of blend uniformity in a stream sampler device using Raman spectroscopy.

This study describes the first implementation of Raman spectrometer in a stream sampler for the in-line monitoring of low drug concentration in poor flowability powder blends. Raman spectra were continuously acquired as the powder blends flowed through the stream sampler operating with a paddle wheel speed of 10 RPM and used to develop the calibration models. A calibration model was developed to quantify caffeine concentration from 1.50 to 4.50% w/w using Partial Least Squares Regression (PLS-R). Three test set blends were used to assess the prediction errors of the calibration model. Caffeine concentration was predicted for the test set blends with a root mean square error of prediction of 0.21% w/w and a low bias of -0.03% w/w. The calibration model showed good prediction performance with an estimated sample mass of 83 mg. Variographic analysis demonstrated the low process variance of the real-time spectral acquisition through minimum practical error and sill values. The results showed the ability of the Raman spectrometer coupled with the stream sampler to monitor low drug concentration for poor flowability blends.

Quantitative analysis of blend uniformity within a Three-Chamber feed frame using simultaneously Raman and Near-Infrared spectroscopy.

This study reports the use of Raman and Near-infrared (NIR) spectroscopy to simultaneously monitor the drug concentration in flowing powder blends within a three-chamber feed frame. The Raman probe was located at the top of the dosing chamber, while the NIR probe was located at the top of the filling chamber. The Raman and NIR spectra were continuously acquired while the powder blends flowed through the feed frame. Calibration models were developed with spectra from a total of five calibration blends ranging in caffeine concentration among 3.50 and 6.50% w/w. These models were optimized to predict three test set blends of 4.00, 5.00, and 6.00% w/w caffeine. The results showed a high predictive ability of the models based on root mean square error of predictions of 0.174 and 0.235% w/w for NIR and Raman spectroscopic models, respectively. Concentration profiles with higher variability were observed for the Raman spectroscopy predictions. An estimate of the mass analyzed by each spectrum showed that a NIR spectrum analyzes approximately 4.5 times the mass analyzed by a Raman spectrum; despite these differences in the mass analyzed, blend uniformity results are equivalent between techniques. Variographic analysis demonstrated that both techniques have significantly low sampling errors for the real-time monitoring process of drug concentration within the feed frame.

Residence time distribution as a traceability method for lot changes in a pharmaceutical continuous manufacturing system.

Residence time distribution (RTD) models were developed to track raw material lots and investigate batch transitions in a continuous manufacturing system. Two raw materials with similar physical properties (granular metformin and lactose) were identified via Principal Component Analysis (PCA) from a library of bulk material properties and used to simulate the switching of lots during production. In-line near-infrared (NIR) spectra were collected with the powder flowing through a chute in a continuous manufacturing system to monitor metformin and lactose concentration in step-change experiments with Partial Least Squares (PLS) models. RTD provided an understanding of raw material propagation through the continuous manufacturing system. Transition times between raw material changes were identified using the results of two multivariate approaches PLS and PCA. The methodology was implemented to discriminate the transition zone in a raw material change, contributing to design control strategies for acceptance and diverting mechanisms.

Real-time concentration monitoring using a compact composite sensor array for in situ quality control of aqueous formulations.

Recent advancements have demonstrated the feasibility of refrigerator-sized pharmaceutical manufacturing platforms (PMPs) for integrated end-to-end manufacturing of active pharmaceutical ingredients (APIs) into formulated drug products. Unlike typical laboratory- or industrial-scale setups, PMPs present unique requirements for process analytical technology (PAT) with respect to versatility, flexibility, and physical size to fit into the PMP space constraints. In this proof of principle study, a novel compact composite sensor array (CCSA) combining ultraviolet (UV) and near infrared (NIR) features at four different wavelengths (280, 340, 600, 860 nm) with temperature measuring capability in a 380 × 30 mm housing (length x diameter, 7 mm diameter at the probe head), were evaluated. The results indicate that the CCSA prototype is capable of measuring the solution and suspension concentrations in aqueous formulations of four model APIs (warfarin sodium isopropanol solvate, lidocaine hydrochloride monohydrate, 6-mercaptopurine monohydrate, acetaminophen) in situ and in real-time with similar accuracy as an established Raman spectrometer commonly applied for method development.

Monitoring of high-load dose formulations based on co-processed and non co-processed excipients.

This work presents the evaluation of a co-processed material for high-load dose formulations and its real-time monitoring by near-infrared (NIR) spectroscopy at the tablet press feed frame. The powder and tableting properties of co-processed material blends were evaluated and compared to the blend of the individual excipients. The formulations with the co-processed material showed excellent flow properties and were superior to the physical blend of individual excipients. Two NIR spectroscopic methods were developed to monitor ibuprofen concentration between 40.0 and 60.0% w/w, one method using a co-processed material as the main excipient and the other using the blend of the individual excipients. The NIR spectra were obtained while the powder blends flowed within a three-chamber feed frame from a Fette 3090 tablet press. The NIR spectroscopic method with the co-processed material presented better performance with significantly lower prediction error. Variographic analysis demonstrated that using the co-processed material considerably reduces the sampling and analytical errors in the in-line determination of ibuprofen. The authors understand that this is the first study where the sampling errors are evaluated as a function of the excipients used in the pharmaceutical formulation. This study demonstrated that selecting a suitable excipient for the formulation helps optimize the manufacturing process, reducing the magnitude of the total measurement error.

An innovative sampling interface for monitoring flowing pharmaceutical powder mixtures.

A chute was designed following the principles of the Theory of Sampling to minimize the variations in powder flow and provide all particles in the flowing blends with the same opportunity of being selected as a sample. The design also reduces the thickness of the chute to allow the analysis of a higher portion of the flowing blends by a near infrared spectrometer. The blends that flowed through the chute had Carr's index values that fluctuated between 23 and 25 percent, indicating passable flowability. A powder fowling evaluation demonstrated that there was no powder accumulation at the inspection window of the chute. The mass flow rate profiles indicated that the system achieves mass steady-state in approximately 30 s and a throughput of 30 kg/h which makes it suitable for continuous manufacturing operations. An in-line NIR calibration model was developed to quantify caffeine concentrations between 1.51 and 4.52 % w/w. The spectra obtained from each experiment had minimal baseline variation. The developed NIR method was robust to throughput changes up to approximately ±7 %. The test blends in the caffeine concentration range between 2.02 % w/w and 4.02 % w/w met the dose uniformity requirements of the Ph.Eur. 9.0, chapter 2.9.47. Variographic analysis was done to estimate the analytical and sampling errors which yielded values below 0.01 (%w/w)2. The obtained results showed that this chute could also be used in a continuous manufacturing line or other applications with flowing powders.

Fractal and Polarization Properties of Light Scattering Using Microcrystalline Pharmaceutical Aggregates.

Fractal and polarization analysis of diffusively scattered light is applied to determine the complex relationship between fractal dimension of structural morphology and concentration of chemically active ingredients in two pharmaceutical mixture systems including a series of binary mixtures of acetaminophen in lactose and three multicomponent blends with a proprietary active ingredient. A robust approach is proposed to identify and filter out multiple- and single-scattering components of scattering indicatrix. The fractal dimension extracted from scattering field reveals complex structural details of the sample, showing strong dependence on low-dose drug concentration in the blend. Low-angle diffraction shows optical "halo" patterns near the angle of specular reflection caused by light refraction in microcrystalline aggregates. Angular measurements of diffuse reflection demonstrate noticeable dependence of Brewster's angle on drug concentration. It is shown that the acetaminophen microcrystals produce scattered light depolarization due to their optical birefringence. The light scattering measurement protocol developed for diffusively scattered light by microcrystalline pharmaceutical compositions provides a novel approach for the pattern recognition, analysis and classification of materials with a low concentration of active chemical ingredients.

Real-time quantification of low-dose cohesive formulations within a sampling interface for flowing powders.

This study investigates the performance of a sampling interface for monitoring cohesive, flowing powder formulations with Hausner's Ratio and Carr's Index higher than 1.5 and 35%, respectively. The sampler device was operated in combination with near-infrared (NIR) spectroscopy to quantify ibuprofen concentrations between 1.5 and 4.5% w/w. NIR spectra also provided essential information to study the process dynamics within the sampler. The 200 spectra per blend obtained demonstrated a continuous powder flow with no evidence of agglomerates or segregation within the sampler for a blend of 6 kg. A NIR calibration model was optimized to predict independent test blends, delivering root mean square error of predictions and bias under 0.1% w/w. The test blends were within specifications according to the requirements of European Pharmacopeia. Variographic analysis demonstrated that the sampler device may determine low drug concentration in cohesive powder blends, presenting sampling errors below 0.011 (%w/w)2. This analysis also demonstrated that an increase in the blend compressibility leads to a slight rise in sampling errors within the sampler device. The sampler device offers statistical robustness in the evaluation of blend uniformity, providing greater confidence in the quality determination of the cohesive powder blends without significantly affecting its flow properties.

In-line monitoring of low drug concentration of flowing powders in a new sampler device.

A novel sampler device for flowing powders was tested to quantify drug concentrations as low as 0.76% w/w in pharmaceutical powder blends. The sampler device was developed based on the powder flow behavior within a tablet press feed frame, following the principles laid down in the Theory of Sampling. Two Near-Infrared (NIR) spectroscopic calibration models were developed with powder blends that varied from 0.52 to 2.52% w/w and 1.51-4.52% w/w. The calibration models were able to determine caffeine concentration in test set blends with root mean square error of predictions and bias below 0.1% w/w. Samples were collected from the sampler device and analyzed by ultraviolet-visible (UV-Vis) to determine the caffeine concentration. A high agreement between the in-line NIR predictions and the sampled UV-Vis results was found. The paddle wheel speed in the sampler can be varied up to ±10% without affecting NIR predictions; however, the models did not respond adequately to a 25% increase in this speed. Variographic analysis showed that the sampler device may quantify low drug concentrations with nugget effects below 0.0050 (%w/w)2. This study demonstrate that the sampler device may handle throughputs up to 45 kg/h, without significantly affecting the physical properties of powder blends.

Method transfer of a near-infrared spectroscopic method for blend uniformity in a poorly flowing and hygroscopic blend.

The challenges in transferring and executing a near-infrared (NIR) spectroscopic method for croscarmellose (disintegrant) in binary blends for a continuous manufacturing (CM) process are presented. This work demonstrates the development of a NIR calibration model and its use to determine the blending parameters needed for binary blends at a development plant and later used to predict CM process blends. The calibration models were developed with laboratory scale powder blends ranging from 4.32%-64.77 (%w/w) of croscarmellose and evaluated using independent test blends. The selected model was then transferred to the continuous manufacturing development site to determine the croscarmellose concentration for spectra collected in real-time. A total of 18 development plant runs were monitored using an in-line NIR spectrometer, however, these spectra showed high baseline variations. The baseline variations were caused by the poor flow of the material within the system. An inconsistent bias which varied from 2.51 to 14.95 (%w/w) was observed in the predictions of croscarmellose. High baseline spectra were eliminated and the bias was significantly reduced by 42-51%. Experiments at lower flow rate speeds did not show significant changes in baseline and bias values showed more consistency. The calibration model was then transferred to two NIR spectrometers installed at-line at the commercial site, where powder samples were collected at the beginning middle and end of each CM plant run. The NIR calibration model predicted disintegrant concentration from the powder samples. Results showed the bias values for the NIR (1) varied from 0.74 to 2.21 (%w/w) and NIR (2) from 0.28 to 3.39 (%w/w). Average concentration values for both equipments were very close to the reference concentration values of 43.18 and 50.98 (%w/w). The study showed the model was able to identify flow issues, identified as baseline shifts, that could be used to alert to problems in the powder bed that may warrant diversion from a production line. These powder flow problems such as air gaps and inconsistent powder bed height affected the NIR spectra collected at the development plant and provided results with high bias. A lower bias was obtained in samples collected at line after blending.

A sampling system for flowing powders based on the theory of sampling.

An innovative chute and stream sampler system for flowing powders has been developed and tested. The system is designed for representative sampling based on the principles of the Theory of Sampling (TOS). The sampling system was used in combination with near infrared (NIR) spectroscopy to determine the drug concentration of flowing powders. The system is comprised of three parts: a chute, a stream sampler and a sample collection port. The NIR spectra were obtained at the chute, before entering the sampler, and as the powder flowed through the stream sampler. Samples were also collected from the sample collection port to be analyzed using an ultraviolet-visible (UV-Vis) reference method to determine drug content. A total of eight pharmaceutical powder blends, ranging in concentration from 10.5(%w/w) to 19.5(%w/w) of caffeine, were used to test the sampling system. Materials were characterized before blends were made to provide information on flow properties. The throughput of the system was between 30 and 35 kg/h based on the flow properties of the blend. Drug concentration was effectively determined at the chute and stream sampler. The NIR calibration models showed low root mean squared errors of prediction, 0.65(%w/w) and 0.51(%w/w), for the chute and stream sampler respectively. The NIR calibration models also showed low bias values -0.36(%w/w) at the chute and 0.057(%w/w) at the stream sampler. Significant agreement was obtained between the results from the nondestructive NIR versus the destructive UV-Vis method. Variographic analysis was performed to estimate the analytical and sampling errors when determining the drug concentration at the chute and stream sampler respectively. The variographic analysis showed low analytical errors, 0.103(%w/w)2 and 0.181(%w/w)2 at the chute and stream sampler respectively. The analysis also showed that the minimum practical error (MPE) was around 0.2(%w/w)2 at both chute and stream sampler.

Feed frame: The last processing step before the tablet compaction in pharmaceutical manufacturing.

The feed frame is a force-feeding device used in the die filling process. The die filling process is crucial within pharmaceutical manufacturing to guarantee the critical quality attributes of the tablets. In recent years, interest in this unit has increased because it can affect the properties of the powder blend and tablets, and because of the success in real time monitoring of powder blend uniformity potential for Process Analytical Technology as described in this review. The review focuses on the recent advances in understanding the powder flow behavior inside the feed frame and how the residence time distribution of the powder within the feed frame is affected by the operating conditions and design parameters. Furthermore, this review also highlights the effect of the paddle wheel design and feed frame process parameters on the tablet weight, the principal variable for measuring die filling performance.

Assessment of blend uniformity in a continuous tablet manufacturing process.

Blend uniformity was monitored throughout a continuous manufacturing (CM) process by near infrared (NIR) spectroscopic measurements of flowing blends and compared to the drug concentration in the tablets. The NIR spectra were obtained through the chute after the blender and within the feed frame, while transmission spectra were obtained for the tablets. The CM process was performed with semi-fine acetaminophen blends at 10.0% (w/w). The blender was operated at 250 RPM, for best performance, and 106 and 495 rpm where a lower mixing efficiency was expected. The variation in blender RPM increased the variation in drug concentration at the chute but not at the feed frame. Statistical results show that the drug concentration of tablets can be predicted, with great accuracy, from blends within the feed frame. This study demonstrated a mixing effect within the feed frame, which contribute to a 60% decrease in the relative standard deviation of the drug concentration, when compared to the chute. Variographic analysis showed that the minimum sampling and analytical error was five times less in the feed frame than the chute. This study demonstrates that the feed frame is an ideal location for monitoring the drug concentration of powder blends for CM processes.

Development of near infrared spectroscopic calibration models for in-line determination of low drug concentration, bulk density, and relative specific void volume within a feed frame.

This study describes the development of a near infrared (NIR) calibration model for real time determination of drug concentration, powder density, and porosity or relative specific void volume (RSVV) of 3.00%w/w acetaminophen blends within a feed frame. The NIR calibration model was developed from 1.50 to 4.50%w/w of acetaminophen, using a high variability of major excipients (from 12.92 to 81.95%w/w) which facilitates the prediction of powder density and RSVV based on near infrared calibration spectra. The model using second derivative as spectral preprocessing explained the changes related to acetaminophen concentration in the first latent variable. The second latent variable was related to changes in concentration of microcrystalline cellulose and lactose in the powder blends. NIR calibrations were also developed based on the bulk density and RSVV of the powder blends using the same design as the API model, due to the physical properties of the particles and their effects on the NIR spectra. The RSVV was predicted for the independent set blends with an RSEP(%) below 4% with a significantly low bias (0.04 cm3/g) from reference values of 1.33 to 1.58 cm3/g. The bulk density model also exhibited excellent predictions with RSEP(%) below 2.6% and significantly low bias (0.01 g/cm3) from reference values of 0.45 to 0.51 g/cm3. The excellent results obtained show the potential of near infrared spectroscopic measurements within the feed frame for a Process Analytical Technology method to control the critical properties such as tablet mass, hardness and dissolution in batch and continuous manufacturing processes.

In line monitoring of the powder flow behavior and drug content in a Fette 3090 feed frame at different operating conditions using Near Infrared spectroscopy.

Near infrared (NIR) spectroscopy was used to determine the drug concentration in 3% (w/w) acetaminophen blends within the complex flow regime of the tablet press feed frame just before tablet compaction. NIR spectra also provided valuable information on the powder flow behavior within the feed frame and were used to track when a process enters or leaves the steady state. A partial least squares regression calibration model was developed with powder mixtures that varied from 1.5 to 4.5% (w/w) by obtaining 135 spectra after steady state for each concentration while the feed frame and die disc operated at 30.5 revolutions per minute (rpm). The calibration model determined drug concentration in validation blends with a root mean square error of prediction and bias below 0.1% (w/w). The robustness of the NIR calibration model was evaluated by determining the effect of variation on the operating conditions (paddle wheel speed and die disc speed) on NIR predictions. This work found that the paddle wheel speed can be increased up to 30% and the die disc speed decrease 10% without affecting NIR predictions. The results demonstrated that paddle wheel speed has a significant effect on the wave powder behavior (frequency and amplitude) but does not have significant effect on the mass hold-up within feed frame. The die disc speed does not affect wave powder behavior but affects significantly the mass hold-up inside the feed frame. This information can be used to reduce the tablet weight variability and ensure that this critical attribute is met.

Process analytical technology in continuous manufacturing of a commercial pharmaceutical product.

The implementation of process analytical technology and continuous manufacturing at an FDA approved commercial manufacturing site is described. In this direct compaction process the blends produced were monitored with a Near Infrared (NIR) spectroscopic calibration model developed with partial least squares (PLS) regression. The authors understand that this is the first study where the continuous manufacturing (CM) equipment was used as a gravimetric reference method for the calibration model. A principal component analysis (PCA) model was also developed to identify the powder blend, and determine whether it was similar to the calibration blends. An air diagnostic test was developed to assure that powder was present within the interface when the NIR spectra were obtained. The air diagnostic test as well the PCA and PLS calibration model were integrated into an industrial software platform that collects the real time NIR spectra and applies the calibration models. The PCA test successfully detected an equipment malfunction. Variographic analysis was also performed to estimate the sampling analytical errors that affect the results from the NIR spectroscopic method during commercial production. The system was used to monitor and control a 28 h continuous manufacturing run, where the average drug concentration determined by the NIR method was 101.17% of label claim with a standard deviation of 2.17%, based on 12,633 spectra collected. The average drug concentration for the tablets produced from these blends was 100.86% of label claim with a standard deviation of 0.4%, for 500 tablets analyzed by Fourier Transform Near Infrared (FT-NIR) transmission spectroscopy. The excellent agreement between the mean drug concentration values in the blends and tablets produced provides further evidence of the suitability of the validation strategy that was followed.